Is Statistical-Learning-Method_Code open source?

Yes — Dod-o/Statistical-Learning-Method_Code is an open-source project tracked on heatdrop.

What language is Statistical-Learning-Method_Code written in?

Dod-o/Statistical-Learning-Method_Code is primarily written in Python.

How popular is Statistical-Learning-Method_Code?

Dod-o/Statistical-Learning-Method_Code has 11.6k stars on GitHub.

Where can I find Statistical-Learning-Method_Code?

Dod-o/Statistical-Learning-Method_Code is on GitHub at https://github.com/Dod-o/Statistical-Learning-Method_Code.

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Dod-o/Statistical-Learning-Method_Code

An algorithm-by-algorithm Python companion to a classic ML text

Hand-rolled Python for the core algorithms in Li Hang's *Statistical Learning Methods*, with comments that map each line back to the book's formulas.

★11.6k stars Python Learning ML Frameworks

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What it does

This repository implements the core algorithms from Li Hang’s Statistical Learning Methods as plain, from-scratch Python. Each file is heavily commented with references back to the book’s formulas, turning the codebase into an executable set of margin notes. Coverage spans supervised staples—Perceptron, SVM, HMM, AdaBoost—and unsupervised methods including PCA, LDA, and PageRank.

The interesting bit

The author explicitly optimizes for readability over performance: the stated goal is to let a learner read the code alongside the textbook and know exactly which formula each branch implements. Several early chapters also ship with PDF blog posts that dissect the math.

Key highlights

Broad coverage of the book’s algorithm roster, including maximum entropy, PLSA, and PageRank
Comment-dense, formula-referenced code; no black-box library wrappers
Pre-processed MNIST dataset included (as a compressed CSV)
Select chapters come with deep-dive PDF blog posts
CC BY-NC-SA 4.0 license

Caveats

Documentation is uneven: early supervised chapters get detailed PDF blogs, while later supervised and all unsupervised chapters are code-only
The non-commercial license prevents commercial reuse
The README is interrupted by unrelated advertisements for API services and offline training courses

Verdict

Students working through Li Hang’s book will find this a readable map between formulas and code. If you need production-grade libraries or permissive licensing, this is strictly pedagogy.

Frequently asked

What is Dod-o/Statistical-Learning-Method_Code?: Hand-rolled Python for the core algorithms in Li Hang's *Statistical Learning Methods*, with comments that map each line back to the book's formulas.
Is Statistical-Learning-Method_Code open source?: Yes — Dod-o/Statistical-Learning-Method_Code is an open-source project tracked on heatdrop.
What language is Statistical-Learning-Method_Code written in?: Dod-o/Statistical-Learning-Method_Code is primarily written in Python.
How popular is Statistical-Learning-Method_Code?: Dod-o/Statistical-Learning-Method_Code has 11.6k stars on GitHub.
Where can I find Statistical-Learning-Method_Code?: Dod-o/Statistical-Learning-Method_Code is on GitHub at https://github.com/Dod-o/Statistical-Learning-Method_Code.